- - 48 Transportation Research Record 870 Economic Impacts of Petroleum Shortages and Implications for the Freight Transportation Industry LARRY R. JOHNSON, RITA E. KNORR, CHRISTOPHER L. SARICKS, AND VEENA B. MENDIRATTA The major economic impacts that result from petroleum supply interruptions and the subsequent effects on the demand for freight transportation are de- scribed. The analysis involved a simulation of the effects of three different levels of fuel supply shortfall on intercity freight transportation. The research included the use of three economic and transportation models to simulate the economic impacts of oil shortfalls and the resulting change in freight transpor- tation demand as expressed in tons shipped, ton miles of travel, and fuel use. Economic effects are discussed for a base case and then for 7, 14, and 23 per- cent petroleum shortfalls. The demand for freight transportation is determined by the output of various commodity sectors that generate traffic for the truck, rail, water, air, and pipeline modes. The effects of various diesel fuel price levels are also examined. The analysis suggests that at low, or controlled, fuel prices the more significant impacts for freight movements will be the reduction in output in the bulk commodity sectors, which are dominated by the waterway and rail modes. At high fuel prices (i.e., equilibrium levels), shipping is signifi- cantly decreased in all commodity sectors, but modal shifts are likely to occur from truck to rail and even from rail to water in some corridors. The United States has experienced significant eco- nomic problems associated with two of the three major interruptions in the world supply of petro- leum--the Arab oil embargo in 1973-1974 and the Iranian revolution in 1979. Less difficulty was encountered with the loss of crude oil due to the Iran-Iraq war. High inventories coupled with re- duced demand have made the loss of those supplies barely noticeable. Saudi Arabia increased its oil production to partially compensate for a reduction in the oil spot-market pr ice in order to eventually produce a unified Organization of Petroleum Export- ing Countries (OPEC) pr ice. Competing economic and political goals in the Middle East cause this region to remain volatile, which suggests that future dis- ruptions in petroleum supply are highly probable, if not inevitable. Petroleum supply shortages produce economic shocks that have a direct effect on the demand for freight transportation. However, the changes in economic activity are not uniform. Some sectors show a dramatic decline in production and sales that goes far beyond the level of the oil shortage, whereas others show no adverse impact or even some moderate gain. To quantify these economic changes, an econometi: ic model and two freight transportation models were used to simulate the effects of three different shortage situations. This section pro- vides a brief discussion of the modeling process. A description of the control forecast and three hypo- thetical oil shortfall cases simulated by the models is included in the following section. The Data Resources, Inc. (DRI), Quarterly Model of the U.S. Economy has been used in this study to analyze the impacts of petroleum shortfalls at the national level. The ORI model is a simultaneous- equations model that includes a circular flow of income and expenditure in the economy. The DRI model provided macroeconomic indicators for the Argonne National Laboratory Freight Respon- sive Accounting for Transportation Energy (FRATE) model to estimate the change in commodities shipped by mode before any contingency actions are initi- ated. The FRATE model calculates annual ton miles of travel (TMT) for commodities, accounts for modal activity, and computes the transportation energy consumed based on economic-sector output levels. The base-year ton-mile estimates for the economic sectors in FRATE are derived from the U.S. Bureau of the Census Commodity Transportation Survey (!.l· The FRATE economic activity sectors are paired with similar sectors in the DRI econometric model in order to apply the projected output growth rates to the base-year ton-mile estimates (1_). The model assumes, for lack of a better indicator, that ton- mile growth is directly related to output growth rates. Traffic estimates for truck, railroad, marine, air, and pipeline modes are calculated based on historic modal-split distributions (1,3-5). Energy intensity values associated ;-ith -each eco- nomic sector are based on the freight mode and the type of service provided by that mode (}_,_!,il. The FRATE economic-sector ton-mile estimates are applied to the energy intensity values for projected energy consumption values. FRATE then aggregates the energy demand of all sectors by type of mode. The third model used in this analysis was the National Freight Demand Model (NAFDEM), developed for Argonne National Laboratory by the Massachusetts Institute of Technology. NAFDEM provides a means to determine shipper response to rate and level-of- service alterations imposed by carriers during fuel shortfall situations. This response could involve a change in the freight mode selected for shipment, a change in the size of shipment, or both. The logic governing the degree and direction of change arises from a utility logit model of freight mode and ship- ment size developed and calibrated to observed shipper behavior by Chiang and others (2). NAFDEM does not include the pipeline mode since it is not applicable for most commodity sectors. A basic premise of NAFDEM is that shippers in any commodity group seek to move more freight by the mode or modes that maximize their total utility. This utility is computed from the mode-specific rate and level-of-service relations to commodity charac- ter is tics developed by Chiang. NAFDEM constructs a utility function for a simulated firm that is de- fined by, or synthesized from, the characteristics of and demand for the commodity it ships. In order to construct the initial utility function, baseline annual commodity use rates by receiving firms; ship- ping distances; shipment sizes; commodity densities, perishability, and value per unit weight; and travel times, rates, and reliabilities by mode must all be defined for the shipper and commodity (these var i- ables largely define the firm). In the modeling process, values for most of these variables are ran- domly selected by using a Monte Carlo procedure from a set of commodity-group-specific ranges (proba- bility density functions), each bounded within a sampling confidence interval centered on the mean value. The baseline modal probabilities estimated by this procedure are assumed to result in the "ob- served" distribution input to the model from a run of FRATE for the appropriate fuel shortfall condi- tions. NAFDEM calculates the perturbations in modal choice and shipment sizes brought about by each syn- thesized shipper's attempt to continue to maximize its total utility after a change in carrier rates and level of service is defined. Computed values of the rate and level-of-service equations developed by Chiang and others (2) are modified by changes in